A novel machining parameter driven modeling method for 3D rough surface on vibrating finishing
Accurate modeling of submicron-scale rough surfaces based on machining parameters represents the forefront of precision manufacturing. Currently, there is limited research on precisely modeling the three-dimensional topography resulting from vibration finishing processes. This study explores a novel...
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Published in | International journal of advanced manufacturing technology Vol. 135; no. 11; pp. 5695 - 5714 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
London
Springer London
01.12.2024
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 0268-3768 1433-3015 |
DOI | 10.1007/s00170-024-14835-7 |
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Abstract | Accurate modeling of submicron-scale rough surfaces based on machining parameters represents the forefront of precision manufacturing. Currently, there is limited research on precisely modeling the three-dimensional topography resulting from vibration finishing processes. This study explores a novel method for modeling rough surfaces in vibration finishing, focusing on a roller as the subject of investigation. The approach considers the elastic and plastic deformation principles of discrete random abrasive particles impacting the workpiece surface. By knowing the normal and tangential velocities of the abrasive particles relative to the workpiece, along with material parameters of both the abrasive particle and workpiece, quantitative formulas are derived. These formulas estimate the depth of permanent deformation caused by individual abrasive particle impacts and calculate the number of particles involved within a specified machining time. The cumulative effect of all particle impacts yields the final three-dimensional surface morphology. Experimental validation is conducted using a roller post-shot peening, comparing its surface morphology before and after processing. The study finds a mere 8.65% average error between the predictive model and experimental results, affirming the model’s efficacy. Furthermore, the influence of abrasive particle diameter and workpiece surface hardness on roughness is analyzed. The three-dimensional topography prediction model proposed in this paper can effectively improve the control ability of vibration finishing process, which has positive guiding significance for production practice. |
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AbstractList | Accurate modeling of submicron-scale rough surfaces based on machining parameters represents the forefront of precision manufacturing. Currently, there is limited research on precisely modeling the three-dimensional topography resulting from vibration finishing processes. This study explores a novel method for modeling rough surfaces in vibration finishing, focusing on a roller as the subject of investigation. The approach considers the elastic and plastic deformation principles of discrete random abrasive particles impacting the workpiece surface. By knowing the normal and tangential velocities of the abrasive particles relative to the workpiece, along with material parameters of both the abrasive particle and workpiece, quantitative formulas are derived. These formulas estimate the depth of permanent deformation caused by individual abrasive particle impacts and calculate the number of particles involved within a specified machining time. The cumulative effect of all particle impacts yields the final three-dimensional surface morphology. Experimental validation is conducted using a roller post-shot peening, comparing its surface morphology before and after processing. The study finds a mere 8.65% average error between the predictive model and experimental results, affirming the model’s efficacy. Furthermore, the influence of abrasive particle diameter and workpiece surface hardness on roughness is analyzed. The three-dimensional topography prediction model proposed in this paper can effectively improve the control ability of vibration finishing process, which has positive guiding significance for production practice. |
Author | Chen, Jiling Zhang, Hao Shao, Wen Tang, Jinyuan Li, Xin |
Author_xml | – sequence: 1 givenname: Hao surname: Zhang fullname: Zhang, Hao organization: State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University – sequence: 2 givenname: Wen surname: Shao fullname: Shao, Wen email: wen.shao@csu.edu.cn, shaowen_2013@163.com organization: State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University – sequence: 3 givenname: Jinyuan surname: Tang fullname: Tang, Jinyuan organization: State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University – sequence: 4 givenname: Xin surname: Li fullname: Li, Xin organization: State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University – sequence: 5 givenname: Jiling surname: Chen fullname: Chen, Jiling organization: State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University |
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Cites_doi | 10.1016/j.cirp.2016.04.011 10.1016/j.ijfatigue.2008.01.005 10.1016/S0007-8506(07)63068-6 10.1007/s00170-023-11134-5 10.1016/j.ijmachtools.2018.10.001 10.1016/j.ijmecsci.2020.105921 10.1016/j.ijmachtools.2016.06.007 10.1016/j.powtec.2008.03.003 10.1016/j.jmapro.2021.10.012 10.1007/s00170-004-2088-5 10.1016/j.cirp.2015.04.004 10.1016/j.ijmecsci.2018.12.041 10.1109/tsm.2003.815199 10.1016/j.ijmecsci.2018.06.024 10.1016/j.promfg.2016.08.045 10.1016/0924-0136(94)01753-N 10.3390/jmmp3010027 10.1016/S0043-1648(02)00016-9 10.1016/j.jmatprotec.2021.117208 10.1007/s00170-014-6194-8 10.1016/j.ijmachtools.2015.02.001 10.1016/j.jmapro.2021.04.002 10.1016/S0890-6955(99)00038-3 10.1504/IJNM.2017.082413 10.1016/j.cirp.2019.04.082 10.1016/j.ijmecsci.2024.109076 10.1016/j.cirp.2017.04.092 10.1016/j.ijmachtools.2024.104197 10.1115/1.2787319 10.1016/j.jmatprotec.2019.116577 10.1016/j.ijmecsci.2014.09.008 10.1007/s00170-018-1639-0 |
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Keywords | Predictive modeling Elastic–plastic deformation Surface topography Roller Vibration finishing |
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SubjectTerms | Abrasive finishing Abrasive machining CAE) and Design Computer-Aided Engineering (CAD Deformation effects Elastic deformation Elastic limit Engineering Error analysis Industrial and Production Engineering Mechanical Engineering Media Management Modelling Morphology Original Article Particle size Plastic deformation Prediction models Predictions Process parameters Surface hardness Three dimensional analysis Topography Vibration analysis Workpieces |
Title | A novel machining parameter driven modeling method for 3D rough surface on vibrating finishing |
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